833 resultados para Work processes
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T. E. Harris was a pioneer par excellence in many fields of probability theory. In this paper, we give a brief survey of the many fundamental contributions of Harris to the theory of branching processes, starting with his doctoral work at Princeton in the late forties and culminating in his fundamental book ``The Theory of Branching Processes,'' published in 1963.
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Hydroxyapatite (HA)-based biocomposites have been widely investigated for a multitude of applications and these studies have been largely driven to improve mechanical properties (toughness and strength) without compromising cytocompatibility properties. Apart from routine cell viability/proliferation analysis, limited efforts have been made to quantify the fate processes (cell proliferation, cell cycle, and cell apoptosis) of human fetal osteoblast (hFOB) cells on HA-based composites, in vitro. In this work, the osteoblast cell fate process has been studied on a model hydroxyapatite-titanium (HA-Ti) system using the flow cytometry. In order to retain both HA and Ti, the novel processing technique, that is, spark plasma sintering, was suitably adopted. The cell fate processes of hFOBs, as evaluated using a flow cytometry, revealed statistically insignificant differences among HA-10 wt % Ti and HA and control (tissue culture polystyrene surface) in terms of osteoblast apoptosis, proliferation index as well as division index. For the first time, we provide quantified flow cytometry results to demonstrate that 10 wt % Ti additions to HA do not have any significant influence on the fate processes of human osteoblast-like cells, in vitro.
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This commentary discusses and summarizes the key highlights of our recently reported work entitled ``Neuronal Differentiation of Embryonic Stem Cell Derived Neuronal Progenitors Can Be Regulated by Stretchable Conducting Polymers.'' The prospect of controlling the mechanical-rigidity and the surface conductance properties offers a unique combination for tailoring the growth and differentiation of neuronal cells. We emphasize the utility of transparent elastomeric substrates with coatings of electrically conducting polymer to realize the desired substrate-characteristics for cellular development processes. Our study showed that neuronal differentiation from ES cells is highly influenced by the specific substrates on which they are growing. Thus, our results provide a better strategy for regulated neuronal differentiation by using such functional conducting surfaces.
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A new representation of spatio-temporal random processes is proposed in this work. In practical applications, such processes are used to model velocity fields, temperature distributions, response of vibrating systems, to name a few. Finding an efficient representation for any random process leads to encapsulation of information which makes it more convenient for a practical implementations, for instance, in a computational mechanics problem. For a single-parameter process such as spatial or temporal process, the eigenvalue decomposition of the covariance matrix leads to the well-known Karhunen-Loeve (KL) decomposition. However, for multiparameter processes such as a spatio-temporal process, the covariance function itself can be defined in multiple ways. Here the process is assumed to be measured at a finite set of spatial locations and a finite number of time instants. Then the spatial covariance matrix at different time instants are considered to define the covariance of the process. This set of square, symmetric, positive semi-definite matrices is then represented as a third-order tensor. A suitable decomposition of this tensor can identify the dominant components of the process, and these components are then used to define a closed-form representation of the process. The procedure is analogous to the KL decomposition for a single-parameter process, however, the decompositions and interpretations vary significantly. The tensor decompositions are successfully applied on (i) a heat conduction problem, (ii) a vibration problem, and (iii) a covariance function taken from the literature that was fitted to model a measured wind velocity data. It is observed that the proposed representation provides an efficient approximation to some processes. Furthermore, a comparison with KL decomposition showed that the proposed method is computationally cheaper than the KL, both in terms of computer memory and execution time.
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This work addresses the problem of estimating the optimal value function in a Markov Decision Process from observed state-action pairs. We adopt a Bayesian approach to inference, which allows both the model to be estimated and predictions about actions to be made in a unified framework, providing a principled approach to mimicry of a controller on the basis of observed data. A new Markov chain Monte Carlo (MCMC) sampler is devised for simulation from theposterior distribution over the optimal value function. This step includes a parameter expansion step, which is shown to be essential for good convergence properties of the MCMC sampler. As an illustration, the method is applied to learning a human controller.
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10 p.
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In this work the state of the art of the automatic dialogue strategy management using Markov decision processes (MDP) with reinforcement learning (RL) is described. Partially observable Markov decision processes (POMDP) are also described. To test the validity of these methods, two spoken dialogue systems have been developed. The first one is a spoken dialogue system for weather forecast providing, and the second one is a more complex system for train information. With the first system, comparisons between a rule-based system and an automatically trained system have been done, using a real corpus to train the automatic strategy. In the second system, the scalability of these methods when used in larger systems has been tested.
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High-resolution orbital and in situ observations acquired of the Martian surface during the past two decades provide the opportunity to study the rock record of Mars at an unprecedented level of detail. This dissertation consists of four studies whose common goal is to establish new standards for the quantitative analysis of visible and near-infrared data from the surface of Mars. Through the compilation of global image inventories, application of stratigraphic and sedimentologic statistical methods, and use of laboratory analogs, this dissertation provides insight into the history of past depositional and diagenetic processes on Mars. The first study presents a global inventory of stratified deposits observed in images from the High Resolution Image Science Experiment (HiRISE) camera on-board the Mars Reconnaissance Orbiter. This work uses the widespread coverage of high-resolution orbital images to make global-scale observations about the processes controlling sediment transport and deposition on Mars. The next chapter presents a study of bed thickness distributions in Martian sedimentary deposits, showing how statistical methods can be used to establish quantitative criteria for evaluating the depositional history of stratified deposits observed in orbital images. The third study tests the ability of spectral mixing models to obtain quantitative mineral abundances from near-infrared reflectance spectra of clay and sulfate mixtures in the laboratory for application to the analysis of orbital spectra of sedimentary deposits on Mars. The final study employs a statistical analysis of the size, shape, and distribution of nodules observed by the Mars Science Laboratory Curiosity rover team in the Sheepbed mudstone at Yellowknife Bay in Gale crater. This analysis is used to evaluate hypotheses for nodule formation and to gain insight into the diagenetic history of an ancient habitable environment on Mars.
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A general review of stochastic processes is given in the introduction; definitions, properties and a rough classification are presented together with the position and scope of the author's work as it fits into the general scheme.
The first section presents a brief summary of the pertinent analytical properties of continuous stochastic processes and their probability-theoretic foundations which are used in the sequel.
The remaining two sections (II and III), comprising the body of the work, are the author's contribution to the theory. It turns out that a very inclusive class of continuous stochastic processes are characterized by a fundamental partial differential equation and its adjoint (the Fokker-Planck equations). The coefficients appearing in those equations assimilate, in a most concise way, all the salient properties of the process, freed from boundary value considerations. The writer’s work consists in characterizing the processes through these coefficients without recourse to solving the partial differential equations.
First, a class of coefficients leading to a unique, continuous process is presented, and several facts are proven to show why this class is restricted. Then, in terms of the coefficients, the unconditional statistics are deduced, these being the mean, variance and covariance. The most general class of coefficients leading to the Gaussian distribution is deduced, and a complete characterization of these processes is presented. By specializing the coefficients, all the known stochastic processes may be readily studied, and some examples of these are presented; viz. the Einstein process, Bachelier process, Ornstein-Uhlenbeck process, etc. The calculations are effectively reduced down to ordinary first order differential equations, and in addition to giving a comprehensive characterization, the derivations are materially simplified over the solution to the original partial differential equations.
In the last section the properties of the integral process are presented. After an expository section on the definition, meaning, and importance of the integral process, a particular example is carried through starting from basic definition. This illustrates the fundamental properties, and an inherent paradox. Next the basic coefficients of the integral process are studied in terms of the original coefficients, and the integral process is uniquely characterized. It is shown that the integral process, with a slight modification, is a continuous Markoff process.
The elementary statistics of the integral process are deduced: means, variances, and covariances, in terms of the original coefficients. It is shown that an integral process is never temporally homogeneous in a non-degenerate process.
Finally, in terms of the original class of admissible coefficients, the statistics of the integral process are explicitly presented, and the integral process of all known continuous processes are specified.
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I. Introductory Remarks
A brief discussion of the overall organization of the thesis is presented along with a discussion of the relationship between this thesis and previous work on the spectroscopic properties of benzene.
II. Radiationless Transitions and Line broadening
Radiationless rates have been calculated for the 3B1u→1A1g transitions of benzene and perdeuterobenzene as well as for the 1B2u→1A1g transition of benzene. The rates were calculated using a model that considers the radiationless transition as a tunneling process between two multi-demensional potential surfaces and assuming both harmonic and anharmonic vibrational potentials. Whenever possible experimental parameters were used in the calculation. To this end we have obtained experimental values for the anharmonicities of the carbon-carbon and carbon-hydrogen vibrations and the size of the lowest triplet state of benzene. The use of the breakdown of the Born-Oppenheimer approximation in describing radiationless transitions is critically examined and it is concluded that Herzberg-Teller vibronic coupling is 100 times more efficient at inducing radiationless transitions.
The results of the radiationless transition rate calculation are used to calculate line broadening in several of the excited electronic states of benzene. The calculated line broadening in all cases is in qualitative agreement with experimental line widths.
III. 3B1u←1A1g Absorption Spectra
The 3B1u←1A1g absorption spectra of C6H6 and C6D6 at 4.2˚K have been obtained at high resolution using the phosphorescence photoexcitation method. The spectrum exhibits very clear evidence of a pseudo-Jahn-Teller distortion of the normally hexagonal benzene molecule upon excitation to the triplet state. Factor group splitting of the 0 – 0 and 0 – 0 + v exciton bands have also been observed. The position of the mean of the 0 – 0 exciton band of C6H6 when compared to the phosphorescence origin of a C6H6 guest in a C6D6 host crystal indicates that the “static” intermolecular interactions between guest and hose are different for C6H6 and C6D6. Further investigation of this difference using the currently accepted theory of isotopic mixed crystals indicates that there is a 2cm-1 shift of the ideal mixed crystal level per hot deuterium atom. This shift is observed for both the singlet and triplet states of benzene.
IV. 3E1u←1A1g, Absorption Spectra
The 3E1u←1A1g absorption spectra of C6H6 and C6D6 at 4.2˚K have been obtained using the phosphorescence photoexcitation technique. In both cases the spectrum is broad and structureless as would be expected from the line broadening calculations.
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This project investigated the production of nitrate (nitrification) by bacteria in lakes. The work was undertaken as nitrification is a key process in the nitrogen cycle and previous estimates of rates of nitrification were unreliable. When different methods were used to estimate rates of nitrification within sediment deposits different results were obtained. Investigation' of specific aspects of these methodologies has allowed some rationalization of these observations and also enabled comparisons of previously published data which, beforehand, was not possible. However, it was not clear which methods gave the most reliable rate estimates. Calculation of a nitrate budget for Grasmere lake indicated that the use of methods which involved the mixing of surface sediments (and therefore disrupted preformed nutrient gradients) overestimated the rate of nitrification. The study concludes that slight changes in the method used to prepare sediment slurries can result in large changes, in the measured nitrifying activity. This makes comparisons between studies, using different methods, extremely difficult. Methods to study sediment nitrification processes which do not disrupt preformed substrate gradients within the sediment provide the most reliable rate estimates.
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This article investigates the convergence properties of iterative processes involving sequences of self-mappings of metric or Banach spaces. Such sequences are built from a set of primary self-mappings which are either expansive or non-expansive self-mappings and some of the non-expansive ones can be contractive including the case of strict contractions. The sequences are built subject to switching laws which select each active self-mapping on a certain activation interval in such a way that essential properties of boundedness and convergence of distances and iterated sequences are guaranteed. Applications to the important problem of stability of dynamic switched systems are also given.
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The past years have seen an increasing debate on cooperation and its unique human character. Philosophers and psychologists have proposed that cooperative activities are characterized by shared goals to which participants are committed through the ability to understand each other’s intentions. Despite its popularity, some serious issues arise with this approach to cooperation. First, one may challenge the assumption that high-level mental processes are necessary for engaging in acting cooperatively. If they are, then how do agents that do not possess such ability (preverbal children, or children with autism who are often claimed to be mind-blind) engage in cooperative exchanges, as the evidence suggests? Secondly, to define cooperation as the result of two de-contextualized minds reading each other’s intentions may fail to fully acknowledge the complexity of situated, interactional dynamics and the interplay of variables such as the participants’ relational and personal history and experience. In this paper we challenge such accounts of cooperation, calling for an embodied approach that sees cooperation not only as an individual attitude toward the other, but also as a property of interaction processes. Taking an enactive perspective, we argue that cooperation is an intrinsic part of any interaction, and that there can be cooperative interaction before complex communicative abilities are achieved. The issue then is not whether one is able or not to read the other’s intentions, but what it takes to participate in joint action. From this basic account, it should be possible to build up more complex forms of cooperation as needed. Addressing the study of cooperation in these terms may enhance our understanding of human social development, and foster our knowledge of different ways of engaging with others, as in the case of autism.
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We present a quantum algorithm to simulate general finite dimensional Lindblad master equations without the requirement of engineering the system-environment interactions. The proposed method is able to simulate both Markovian and non-Markovian quantum dynamics. It consists in the quantum computation of the dissipative corrections to the unitary evolution of the system of interest, via the reconstruction of the response functions associated with the Lindblad operators. Our approach is equally applicable to dynamics generated by effectively non-Hermitian Hamiltonians. We confirm the quality of our method providing specific error bounds that quantify its accuracy.
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221 p.